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您的检索式：作者名="Saima Shaheen"
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| 1 | GC/GCMS analysis of the petroleum ether and dichloromethane extracts of Moringa oleifera roots显示文摘Objective:To explore the phytochemical constituents from petroleum ether and diehloromethane extracts of Moringa oleifera(M.oleufera)roots using GC/GC—MS.Methods:A total of 5.11 kg fresh and undried crashed root of M.oleifera were cut into small pieces and extracted with petroleum ether and diehloromethane(20 L.each) at room temperature for 2 d.The concentrated extracts were subjected to their GC—MS analysis.Results:The GC-MS analysis of the petroleum ether and diehloromethane extracts of M.oleifern roots,which showed promising biological activities,has resulted in the identification 102 compounds.These constituents belong to 15 classes of compounds including hydrocarbons,fatty acids,esters,alcohols,isolhioeyanate.thiocyanale,pyrazine,aromalics.alkamides.cyanides,steroids,halocompounds.urea and N-hydroxyimine derivatives,unsaturated alkenamides.alkyne and indole.GC/GC-MS studies on petroleum ether extraet of the roots revealed that it contained 39 compounds,belonging to nine classes.Cyclooctasulfur S8 has been isolated as a pure compound from the extract.The major compounds identified from petroleum ether extract were trans-13-clocosene(37.9%).nonacosane(32.6%).cycloartenol(28.6%) nonadecanoic acid(13.9%) and cyclooctasulfur S8(13.9%).Dichloromethane extract of the roots was composed of 63 compounds of which nasimizinol(58.8%) along with oleic acid(46.5%),N—benzyl-N-(7—cyanato heptanamide(38.3%),N—benzyl-N—(1—chlorononyl) amide(30.3%),bis[3—benzyl prop-2-ene]-1-one(19.5%) and N.N-dibeuzyl—2-ene pent 1.5—diamide(11.6%) were the main constituents.Conclusions:This study helps to predict the formula and structure of active molecules which can be used as drugs.This result also enhances the traditional usage of M.oleifera which possesses a number of bioactive compounds. | Shaheen Faizi saima sumbul Muhammed Ali Versiani Rubeena Saleem Aisha Sana Hira Siddiqui | 2014 | Asian Pacific Journal of Tropical Biomedicine2014，4，8： | 2 |
| 2 | Carbon tetrachloride-induced nephrotoxicity in rats: Protective role of Digera muricata显示文摘 | Muhammad R. Khan Wajiha Rizvi Gul N. Khan Rahmat A. Khan Saima Shaheen | 2008 | Journal of Ethnopharmacology2008，，1： | 1 |
| 3 | B^(2)C^(3)NetF^(2):Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection显示文摘Currently,the improvement in AI is mainly related to deep learning techniques that are employed for the classification,identification,and quantification of patterns in clinical images.The deep learning models show more remarkable performance than the traditional methods for medical image processing tasks,such as skin cancer,colorectal cancer,brain tumour,cardiac disease,Breast cancer(BrC),and a few more.The manual diagnosis of medical issues always requires an expert and is also expensive.Therefore,developing some computer diagnosis techniques based on deep learning is essential.Breast cancer is the most frequently diagnosed cancer in females with a rapidly growing percentage.It is estimated that patients with BrC will rise to 70%in the next 20 years.If diagnosed at a later stage,the survival rate of patients with BrC is shallow.Hence,early detection is essential,increasing the survival rate to 50%.A new framework for BrC classification is presented that utilises deep learning and feature optimization.The significant steps of the presented framework include(i)hybrid contrast enhancement of acquired images,(ii)data augmentation to facilitate better learning of the Convolutional Neural Network(CNN)model,(iii)a pre‐trained ResNet‐101 model is utilised and modified according to selected dataset classes,(iv)deep transfer learning based model training for feature extraction,(v)the fusion of features using the proposed highly corrected function‐controlled canonical correlation analysis approach,and(vi)optimal feature selection using the modified Satin Bowerbird Optimization controlled Newton Raphson algorithm that finally classified using 10 machine learning classifiers.The experiments of the proposed framework have been carried out using the most critical and publicly available dataset,such as CBISDDSM,and obtained the best accuracy of 94.5%along with improved computation time.The comparison depicts that the presented method surpasses the current state‐ofthe‐art approaches. | Mamuna Fatima Muhammad Attique Khan Saima Shaheen Nouf Abdullah Almujally Shui‐Hua Wang | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
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